Esempio n. 1
0
import time

from pyqtgraph.opengl import GLViewWidget, MeshData
from pyqtgraph.opengl.items.GLMeshItem import GLMeshItem

from PyQt5.QtGui import QApplication


volume = load(os.path.join(os.path.split(__file__)[0], 'data/input/sample.npy'))


t0 = time.time()
vertices, normals, faces = march(volume, 0)  # zero smoothing rounds
smooth_vertices, smooth_normals, faces = march(volume, 4)  # 4 smoothing rounds
t1 = time.time()
print("took", t1 - t0, "sec")

app = QApplication([])
view = GLViewWidget()

mesh = MeshData(vertices / 100.0, faces)  # scale down - otherwise camera is misplaced
# or mesh = MeshData(smooth_vertices / 100, faces)
mesh._vertexNormals = normals
# or mesh._vertexNormals = smooth_normals

item = GLMeshItem(meshdata=mesh, color=[1, 0, 0, 1], shader="normalColor")

view.addItem(item)
view.show()
app.exec_()
Esempio n. 2
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        project = self.compute_projection()

        hsize = SIZE // 2
        for xi in range(-hsize, hsize + 1):
            for yi in range(-hsize, hsize + 1):
                if xi == -hsize and yi == -hsize:
                    # skip one corner for visual orientation
                    continue
                vec3 = QtGui.QVector3D(xi, yi, 0)
                pos = project.map(vec3).toPointF()
                painter.drawEllipse(pos, 1, 1)


pg.mkQApp("GLPainterItem Example")
glv = GLViewWidget()
glv.show()
glv.setWindowTitle('pyqtgraph example: GLPainterItem')
glv.setCameraPosition(distance=50, elevation=90, azimuth=0)

griditem = GLGridItem()
griditem.setSize(SIZE, SIZE)
griditem.setSpacing(1, 1)
glv.addItem(griditem)

axisitem = GLAxisItem()
axisitem.setSize(SIZE / 2, SIZE / 2, 1)
glv.addItem(axisitem)

paintitem = GLPainterItem()
glv.addItem(paintitem)
Esempio n. 3
0
import time

from pyqtgraph.opengl import GLViewWidget, MeshData
from pyqtgraph.opengl.items.GLMeshItem import GLMeshItem

from PyQt5.QtGui import QApplication

volume = load(os.path.join(
    os.path.split(__file__)[0], 'data/input/sample.npy'))

t0 = time.time()
vertices, normals, faces = march(volume, 0)  # zero smoothing rounds
smooth_vertices, smooth_normals, faces = march(volume, 4)  # 4 smoothing rounds
t1 = time.time()
print("took", t1 - t0, "sec")

app = QApplication([])
view = GLViewWidget()

mesh = MeshData(vertices / 100.0,
                faces)  # scale down - otherwise camera is misplaced
# or mesh = MeshData(smooth_vertices / 100, faces)
mesh._vertexNormals = normals
# or mesh._vertexNormals = smooth_normals

item = GLMeshItem(meshdata=mesh, color=[1, 0, 0, 1], shader="normalColor")

view.addItem(item)
view.show()
app.exec_()
class PoseEstimation(object):
    @staticmethod
    def getframe(option):
        image = None
        ret_val = 0
        camera = 0
        if option == "camera":
            cam = cv.VideoCapture(camera)
            ret_val, image = cam.read()
        elif option == "kinect":
            image, ret_val = freenect.sync_get_video()
            image = cv.cvtColor(image, cv.COLOR_RGB2BGR)
        elif option.__contains__("/"):
            image = cv.imread(option)
        elif option == "camera_image":
            print("after waiting")
            time.sleep(5)
            print("before waiting")
            cam = cv.VideoCapture(camera)
            ret_val, image = cam.read()
        return image, ret_val

    # creating window inilatizing graph objects
    def __init__(self, args, option='camera'):
        self.args = args
        self.fpsTime = 0
        self.option = option
        self.app = QtGui.QApplication(sys.argv)
        self.window = GLViewWidget()
        self.window.setGeometry(0, 150, 1920, 1080)
        self.window.setCameraPosition(distance=50, elevation=8)
        self.window.setWindowTitle("3D Pose Estimation")
        self.window.show()
        gx = GLGridItem()
        gy = GLGridItem()
        gz = GLGridItem()
        gx.rotate(90, 0, 1, 0)
        gy.rotate(90, 1, 0, 0)
        gx.translate(-10, 0, 0)
        gy.translate(0, -10, 0)
        gz.translate(0, 0, -10)
        self.window.addItem(gx)
        self.window.addItem(gy)
        self.window.addItem(gz)
        self.lines = {}
        keypoints = []
        self.connection = [[0, 1], [1, 2], [2, 3], [0, 4], [4, 5], [5, 6],
                           [0, 7], [7, 8], [8, 9], [9, 10], [8, 11], [11, 12],
                           [12, 13], [8, 14], [14, 15], [15, 16]]
        self.w, self.h = model_wh(self.args.resize)

        if self.w > 0 and self.h > 0:
            self.e = TfPoseEstimator(get_graph_path(self.args.model),
                                     target_size=(self.w, self.h),
                                     trt_bool=str2bool(self.args.tensorrt))
        else:
            self.e = TfPoseEstimator(get_graph_path(self.args.model),
                                     target_size=(432, 368),
                                     trt_bool=str2bool(self.args.tensorrt))

        print(self.args.option)
        image, ret_val = PoseEstimation.getframe(self.args.option)

        self.poseLifting = Prob3dPose(
            'lifting/prob_model/prob_model_params.mat')
        try:

            keypoints = self.mesh(image)
        except AssertionError:
            print("body not in image")
            keypoints = np.zeros((17, 3))
        except Exception:
            print("General exception")
            keypoints = np.zeros((17, 3))

        # self.lines = {}
        # self.connection = [
        #     [13, 16]
        # ]
        # p = []
        # p.append(keypoints[13])
        # p.append(keypoints[16])
        # p = np.array(p)
        finally:
            self.points = GLScatterPlotItem(
                pos=np.array(np.array(keypoints)),
                color=glColor((12, 255, 0)),
                size=15,
            )
            self.window.addItem(self.points)
            for n, pts in enumerate(self.connection):
                self.lines[n] = GLLinePlotItem(pos=np.array(
                    [keypoints[p] for p in pts]),
                                               color=glColor((0, 0, 255)),
                                               width=3,
                                               antialias=True)
                self.window.addItem(self.lines[n])

    def mesh(self, image):
        # image_h, image_w = image.shape[:2]

        width = 640
        height = 480
        pose_2d_mpiis = []
        visibilities = []

        humans = self.e.inference(image,
                                  resize_to_default=(self.w > 0
                                                     and self.h > 0),
                                  upsample_size=self.args.resize_out_ratio)
        image = TfPoseEstimator.draw_humans(image, humans, imgcopy=False)
        cv.putText(image, "FPS: %f" % (1.0 / (time.time() - self.fpsTime)),
                   (10, 10), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
        cv.imshow('tf-pose-estimation result', image)
        self.fpsTime = time.time()

        # image = TfPoseEstimator.draw_humans(image, humans, imgcopy=False)
        # cv2.putText(image,
        #             "FPS: %f" % (1.0 / (time.time() - terrain.fps_time)),
        #             (10, 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
        #             (0, 255, 0), 2)
        # cv2.imshow('tf-pose-estimation result', image)
        # terrain.fps_time = time.time()
        # cv2.waitKey(1)

        for human in humans:
            pose_2d_mpii, visibility = common.MPIIPart.from_coco(human)
            pose_2d_mpiis.append([(int(y * height + 0.5), int(x * width + 0.5))
                                  for x, y in pose_2d_mpii])
            visibilities.append(visibility)

        pose_2d_mpiis = np.array(pose_2d_mpiis)
        visibilities = np.array(visibilities)
        transformed_pose2d, weights = self.poseLifting.transform_joints(
            pose_2d_mpiis, visibilities)
        pose_3d = self.poseLifting.compute_3d(transformed_pose2d, weights)

        keypoints = pose_3d[0].transpose()
        keypoints = keypoints / 100
        print(" \n")

        print(keypoints)
        return keypoints

    """
    return 3d keypoints

    """

    def update(self):
        """ tf.constant([123]) + tf.constant([321])
                update the mesh and shift the noise each time
                """
        # ret_val, image = terrain.get_video()
        # ret_val, image = self.cam.read()
        if cv.waitKey(1) & 0xFF == 27:
            cv.destroyAllWindows()
            sys.exit()

        keypoints = []
        image, ret_val = PoseEstimation.getframe(self.args.option)
        try:
            keypoints = self.mesh(image)
        except AssertionError:
            print("body not in image")
            keypoints = np.zeros((17, 3))
        except Exception:
            print("General exception")
            keypoints = np.zeros((17, 3))
        finally:
            self.points.setData(pos=np.array(keypoints))
            for n, pts in enumerate(self.connection):
                self.lines[n].setData(pos=np.array([keypoints[p]
                                                    for p in pts]))

    """
        update graph all graph objects
    """

    def start(self):
        if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
            QtGui.QApplication.instance().exec_()

    def animation(self, frametime=10):
        """u
        calls the update method to run in a loop
        """
        if not (self.option.__contains__("/")
                or self.option == "camera_image"):
            timer = QtCore.QTimer()
            timer.timeout.connect(self.update)
            timer.start(frametime)
        self.start()